{"id":130305,"date":"2024-08-06T10:36:17","date_gmt":"2024-08-06T09:36:17","guid":{"rendered":"https:\/\/www.artefact.com\/?post_type=blog&#038;p=130305"},"modified":"2024-10-29T09:02:14","modified_gmt":"2024-10-29T09:02:14","slug":"bnp-paribas-giskard-mistral-ai-google-cloud-at-ai-for-finance-by-artefact-ai-language-models-for-businesses-across-customer-support","status":"publish","type":"blog","link":"https:\/\/www.artefact.com\/br\/blog\/bnp-paribas-giskard-mistral-ai-google-cloud-at-ai-for-finance-by-artefact-ai-language-models-for-businesses-across-customer-support\/","title":{"rendered":"BNP PARIBAS, GISKARD, MISTRAL AI &amp; GOOGLE CLOUD na AI for Finance by Artefact - Modelos de linguagem de IA para empresas em todo o suporte ao cliente"},"content":{"rendered":"<p><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--link_color: var(--awb-color6);--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-background-color:var(--awb-color1);--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:calc( 1440px + 20px );margin-left: calc(-20px \/ 2 );margin-right: calc(-20px \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:10px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:10px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:10px;--awb-spacing-left-medium:10px;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:10px;--awb-spacing-left-small:10px;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1 description\" style=\"--awb-text-color:var(--awb-color5);--awb-text-font-family:&quot;PT Serif&quot;;--awb-text-font-style:normal;--awb-text-font-weight:400;\"><p>C\u00fapula de IA para finan\u00e7as por Artefact - 17 de setembro de 2024 - Paris<\/p>\n<p>Principais aprendizados do painel de discuss\u00e3o com Hugues Even, Diretor do Grupo Data do BNP Paribas, Matteo Dora, CTO da Giskard, Guillaume Bour, Diretor de Enterprise EMEA da Mistral AI, Anne-Laure Giret, Diretora do Google Cloud AI GTM, EMEA South do Google Cloud, e Hanan Ouazan, S\u00f3cio e L\u00edder de IA Generativa da Artefact.<\/p>\n<\/div><\/div><\/div><\/div><\/div><article class=\"fusion-fullwidth fullwidth-box fusion-builder-row-2 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--link_color: var(--awb-color6);--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-background-color:var(--awb-color1);--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-justify-content-center fusion-flex-content-wrap\" style=\"max-width:calc( 1440px + 20px );margin-left: calc(-20px \/ 2 );margin-right: calc(-20px \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:10px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:10px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:10px;--awb-spacing-left-medium:10px;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:10px;--awb-spacing-left-small:10px;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-video fusion-youtube\" style=\"--awb-max-width:670px;--awb-max-height:377px;--awb-align-self:center;--awb-width:100%;\"><div class=\"video-shortcode\"><div class=\"fluid-width-video-wrapper\" style=\"padding-top:56.27%;\" ><iframe title=\"Reprodutor de v\u00eddeo do YouTube 1\" src=\"https:\/\/www.youtube.com\/embed\/93jwHVHvidg?wmode=transparent&autoplay=0\" width=\"670\" height=\"377\" allowfullscreen allow=\"autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture;\"><\/iframe><\/div><\/div><\/div><div class=\"fusion-title title fusion-title-1 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Modelos de linguagem de IA aprimorando o atendimento ao cliente<\/h2><\/div><div class=\"fusion-text fusion-text-2\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Esta discuss\u00e3o destaca o papel transformador dos modelos de linguagem de IA no atendimento ao cliente, com foco em suas aplica\u00e7\u00f5es e desafios reais em v\u00e1rios setores, especialmente o banc\u00e1rio. A conversa enfatiza a implanta\u00e7\u00e3o da IA para automatizar e aprimorar as intera\u00e7\u00f5es com o cliente, como por meio de canais de e-mail e voz, com ferramentas que entendem o contexto, priorizam tarefas e sugerem respostas, melhorando assim a efici\u00eancia e a satisfa\u00e7\u00e3o do cliente.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-2 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">IA auxiliando no processamento de e-mail e voz<\/h2><\/div><div class=\"fusion-text fusion-text-3\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Hugues compartilha como a IA auxilia no processamento de e-mails, categorizando, priorizando e encaminhando-os, al\u00e9m de sugerir respostas para revis\u00e3o. Para intera\u00e7\u00f5es de voz, a IA gera resumos p\u00f3s-chamada, itens de a\u00e7\u00e3o e insights que podem ser usados em reuni\u00f5es futuras. Essas ferramentas ajudam os bancos a melhorar a qualidade do servi\u00e7o, analisando o conte\u00fado e o tom das intera\u00e7\u00f5es, indo al\u00e9m dos m\u00e9todos tradicionais de feedback do cliente.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-3 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">IA simplificando os principais processos banc\u00e1rios<\/h2><\/div><div class=\"fusion-text fusion-text-4\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>A conversa tamb\u00e9m aborda o papel da IA nos principais processos banc\u00e1rios, como pedidos de empr\u00e9stimo e integra\u00e7\u00e3o de clientes. A IA, usando modelos de linguagem e vis\u00e3o computacional, ajuda a verificar documentos e a cruzar informa\u00e7\u00f5es para simplificar esses processos. Os participantes destacam como a fun\u00e7\u00e3o da IA generativa est\u00e1 evoluindo de chatbots simples e com scripts para assistentes de conversa\u00e7\u00e3o avan\u00e7ados que lidam com uma ampla gama de consultas e oferecem um servi\u00e7o mais personalizado.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-4 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Transi\u00e7\u00e3o para assistentes de conversa\u00e7\u00e3o com tecnologia de LLMs<\/h2><\/div><div class=\"fusion-text fusion-text-5\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Uma das principais conclus\u00f5es da discuss\u00e3o \u00e9 a transi\u00e7\u00e3o para assistentes de conversa\u00e7\u00e3o alimentados por grandes modelos de linguagem (LLMs), que oferecem respostas mais din\u00e2micas do que os chatbots anteriores. No entanto, esses modelos precisam ser ajustados para contextos e setores espec\u00edficos, exigindo ajustes como a adapta\u00e7\u00e3o de baixo n\u00edvel. A discuss\u00e3o ressalta a import\u00e2ncia de manter o controle sobre esses sistemas de IA, especialmente com o data sens\u00edvel, e destaca as colabora\u00e7\u00f5es com provedores de IA como a Mistral para garantir a seguran\u00e7a e o desempenho do data.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-5 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Desafios de dimensionar a IA na produ\u00e7\u00e3o<\/h2><\/div><div class=\"fusion-text fusion-text-6\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>O dimensionamento da IA na produ\u00e7\u00e3o apresenta desafios, como data governance, desempenho e seguran\u00e7a. Manter a efici\u00eancia e a explicabilidade dos modelos de IA e, ao mesmo tempo, garantir a seguran\u00e7a cibern\u00e9tica s\u00e3o essenciais para a implanta\u00e7\u00e3o em grande escala. A discuss\u00e3o observa a necessidade de atualiza\u00e7\u00f5es cont\u00ednuas do modelo para atender \u00e0s crescentes demandas regulat\u00f3rias e dos clientes, e que a educa\u00e7\u00e3o do usu\u00e1rio sobre as ferramentas de IA \u00e9 fundamental para o sucesso.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-6 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Otimiza\u00e7\u00e3o do tamanho do modelo para efici\u00eancia de custo<\/h2><\/div><div class=\"fusion-text fusion-text-7\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Para enfrentar os desafios de desempenho da IA, Guillaume Bour explica que reduzir o tamanho do modelo e, ao mesmo tempo, manter a precis\u00e3o e a rela\u00e7\u00e3o custo-benef\u00edcio \u00e9 fundamental para o dimensionamento. Eles tamb\u00e9m mencionam que a combina\u00e7\u00e3o de modelos pequenos com fluxos de trabalho orquestrados pode otimizar o desempenho, reduzindo os custos sem sacrificar a qualidade. A observabilidade e os sistemas de monitoramento s\u00e3o cruciais para manter esses modelos em ambientes de produ\u00e7\u00e3o em tempo real.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-7 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Atenuando a alucina\u00e7\u00e3o da IA por meio de testes rigorosos<\/h2><\/div><div class=\"fusion-text fusion-text-8\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Por fim, \u00e9 discutida a quest\u00e3o da \u201calucina\u00e7\u00e3o\u201d da IA, que fornece informa\u00e7\u00f5es incorretas. Testes rigorosos s\u00e3o essenciais para evitar esses erros nas intera\u00e7\u00f5es com os clientes. As colabora\u00e7\u00f5es entre empresas como o BNP e a Discard garantem que os sistemas de IA sejam exaustivamente testados antes da implementa\u00e7\u00e3o para reduzir os riscos. O monitoramento p\u00f3s-implanta\u00e7\u00e3o tamb\u00e9m \u00e9 fundamental para identificar e resolver problemas ao longo do tempo, pois as mudan\u00e7as nas demandas dos clientes, nas regulamenta\u00e7\u00f5es e no ambiente externo afetam o desempenho da IA.<\/p>\n<\/div><\/div><\/div><\/div><\/article><\/p>","protected":false},"excerpt":{"rendered":"<p>Principais aprendizados do painel de discuss\u00e3o com Hugues Even, Diretor do Grupo Data do BNP Paribas, Matteo Dora, CTO da Giskard, Guillaume Bour, Diretor de Enterprise EMEA da Mistral AI, Anne-Laure Giret, Diretora do Google Cloud AI GTM, EMEA South do Google Cloud, e Hanan Ouazan, S\u00f3cio e L\u00edder de IA Generativa da Artefact.<\/p>","protected":false},"featured_media":130306,"parent":0,"template":"","meta":{"_acf_changed":false,"ep_exclude_from_search":false},"blog-category":[21930],"blog-language":[2991],"class_list":["post-130305","blog","type-blog","status-publish","has-post-thumbnail","hentry","blog-category-finance","blog-language-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog\/130305","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog"}],"about":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/types\/blog"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/media\/130306"}],"wp:attachment":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/media?parent=130305"}],"wp:term":[{"taxonomy":"blog-category","embeddable":true,"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog-category?post=130305"},{"taxonomy":"blog-language","embeddable":true,"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog-language?post=130305"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}